According to @data_and_ai, out-of-the-box PyTorch models continue training even when the underlying infrastructure experiences failures, raising concerns about model reliability and consistency in AI-driven crypto trading systems (source: @data_and_ai). This persistent training behavior could result in unreliable trading signals for cryptocurrencies like BTC and ETH, potentially increasing risk for algorithmic traders relying on AI-powered strategies.